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The Predictive Power of the Yield Curve across Countries and Time

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  • Menzie D. Chinn
  • Kavan J. Kucko

Abstract

In recent years, there has been renewed interest in the yield curve (or alternatively, the term premium) as a predictor of future economic activity. In this paper, we re-examine the evidence for this predictor, both for the United States, as well as European countries. We examine the sensitivity of the results to the selection of countries, and time periods. We find that the predictive power of the yield curve has deteriorated in recent years. However there is reason to believe that European country models perform better than non-European countries when using more recent data. In addition, the yield curve proves to have predictive power even after accounting for other leading indicators of economic activity.

Suggested Citation

  • Menzie D. Chinn & Kavan J. Kucko, 2010. "The Predictive Power of the Yield Curve across Countries and Time," NBER Working Papers 16398, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:16398
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    References listed on IDEAS

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    1. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, August.
    2. Glenn D. Rudebusch & Eric T. Swanson & Tao Wu, 2006. "The Bond Yield "Conundrum" from a Macro-Finance Perspective," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 24(S1), pages 83-109, December.
    3. Lucio Sarno & Giorgio Valente, 2009. "Exchange Rates and Fundamentals: Footloose or Evolving Relationship?," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 786-830, June.
    4. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
    5. Jan J. J. Groen & George Kapetanios, 2009. "Model selection criteria for factor-augmented regressions," Staff Reports 363, Federal Reserve Bank of New York.
    6. Francis E. Warnock & Veronica C. Warnock, 2005. "International Capital Flows and U.S. Interest Rates," The Institute for International Integration Studies Discussion Paper Series iiisdp103, IIIS.
    7. Plosser, Charles I. & Geert Rouwenhorst, K., 1994. "International term structures and real economic growth," Journal of Monetary Economics, Elsevier, vol. 33(1), pages 133-155, February.
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    Citations

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    Cited by:

    1. Chris Florakis & Gianluigi Giorgioni & Alexandros Kostakis & Costas Milas, 2012. "The Impact of Stock Market Illiquidity on Real UK GDP Growth," Working Paper series 65_12, Rimini Centre for Economic Analysis.
    2. Aguiar-Conraria, Luís & Martins, Manuel M.F. & Soares, Maria Joana, 2012. "The yield curve and the macro-economy across time and frequencies," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1950-1970.
    3. Periklis Gogas & Theophilos Papadimitriou & Maria Matthaiou & Efthymia Chrysanthidou, 2015. "Yield Curve and Recession Forecasting in a Machine Learning Framework," Computational Economics, Springer;Society for Computational Economics, vol. 45(4), pages 635-645, April.
    4. Ang, James & Smedema, Adam, 2011. "Financial flexibility: Do firms prepare for recession?," Journal of Corporate Finance, Elsevier, vol. 17(3), pages 774-787, June.
    5. Kuosmanen, Petri & Vataja, Juuso, 2014. "Forecasting GDP growth with financial market data in Finland: Revisiting stylized facts in a small open economy during the financial crisis," Review of Financial Economics, Elsevier, vol. 23(2), pages 90-97.
    6. Christiansen, Charlotte, 2013. "Predicting severe simultaneous recessions using yield spreads as leading indicators," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1032-1043.
    7. Kuosmanen, Petri & Nabulsi, Nasib & Vataja, Juuso, 2015. "Financial variables and economic activity in the Nordic countries," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 368-379.
    8. Stijn Claessens & M. Ayhan Kose, 2017. "Asset prices and macroeconomic outcomes: A survey," CAMA Working Papers 2017-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. repec:eee:riibaf:v:42:y:2017:i:c:p:295-303 is not listed on IDEAS
    10. De Pace, Pierangelo & Weber, Kyle D., 2016. "The time-varying leading properties of the high yield spread in the United States," International Journal of Forecasting, Elsevier, vol. 32(1), pages 203-230.
    11. Francis Bismans & Reynald Majetti, 2013. "Forecasting recessions using financial variables: the French case," Empirical Economics, Springer, vol. 44(2), pages 419-433, April.
    12. Kishor, N. Kundan & Koenig, Evan F., 2010. "Yield spreads as predictors of economic activity: a real-time VAR analysis," Working Papers 1008, Federal Reserve Bank of Dallas.
    13. repec:kap:ecopln:v:50:y:2017:i:3:d:10.1007_s10644-017-9212-7 is not listed on IDEAS
    14. Florackis, Chris & Giorgioni, Gianluigi & Kostakis, Alexandros & Milas, Costas, 2014. "On stock market illiquidity and real-time GDP growth," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 210-229.
    15. Samuel Carrasco & Luis Ceballos & Jessica Mena, 2016. "Estimación de la estructura de tasas de interés en Chile," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 19(1), pages 58-75, April.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects

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